Australian researchers: G'day, pathways

QFAB selects Ingenuity Systems' IPA in multiyear deal for systems biology effort

Amy Swinderman
BRISBANE, Australia—The Queensland Facility for AdvancedBioinformatics (QFAB), an interdisciplinary research consortium established tohelp scientists with their bioinformatics requirements, announced in Octoberthat it has entered into a multi-year deal to use Ingenuity Pathway Analysis(IPA), a biological and chemical systems modeling software solution developed byIngenuity Systems, to enhance its data analysis and interpretation offerings.
 
Under the agreement, announced Oct. 6, IPA will beintegrated into QFAB's Integrated Systems Biology platform, which has beenfunded by the Australian Research Council, the Australian Stem Cell Centre andother institutions, and play a major part in QFAB's initiative to enable theglobal efforts of biotechnology, research biology, drug discovery andtranslational medicine. Financial details of the partnership were not disclosed.
 
 
According to Jeremy Barker, CEO of QFAB, the consortium wasestablished to ease the data capture and management, experimental design andanalysis challenges experienced by a broad range of collaborators, includinggroups from the agricultural, biotechnology and biomedical sectors. The SystemsBiology Platform that QFAB is developing aims to characterize and understandthe complex biomolecular networks that control biological processes in cells,tissues or whole organisms. All are based on high-throughput biological dataarising from genomics, transcriptomics and/or proteomics, and all require thediscovery, inference, analysis, modeling and/or simulation of biomolecularnetworks, including those involved in gene expression, regulation,intracellular trafficking, development and disease.
 
 
As part of the bioinformatics platform, IPA will serve asthe primary solution to model, analyze and identify key insights fromhigh-throughput biomolecular data and curated datasets relating to health,biotechnology and environmental processes. IPA will also help explorebiomolecular network models and facilitate experimental validation, Barkersays.
 
 
"Some of our collaborators have been using IPA for a numberof years and requested that we include this in the development of our systemsbiology platform," he says. "It also fits into our philosophy of using'best-of-breed' and relevant technology, whether that be open source orcommercial software.  We choose touse software that is relevant to the research work that we are engaged in andwhere necessary also develop our own."
 
IPA will be provided by Ingenuity Systems and MillenniumScience, the company's exclusive distributor for Australia and New Zealand. IPAis an all-in-one software application that enables researchers to model,analyze and understand the complex biological and chemical systems at the coreof life science research. The software's search capabilities provide users withaccess to the highest quality detail-rich knowledge available on genes, drugs,chemicals, protein families, cellular and disease processes, and signaling andmetabolic pathways. IPA supports analysis of data from all experimentalplatforms, and is used at all stages of the drug discovery and developmentprocess, including target identification and validation, biomarker discovery,molecular toxicology, metabolomics and pharmacogenomics. IPA has been broadlyadopted and cited in hundreds of peer-reviewed journals.
 
"IPA is unique because it draws upon the Ingenuity KnowledgeBase, a database of manually curated and structured biological and chemicalrelationships, which we call Findings," explains Heidi Bullock, director ofmarketing for Ingenuity Systems. "Ingenuity Findings, unlike flat text recordsor other databases, are highly structured to capture detailed biologicalcontext and relationships (such as sites of post-translational modifications,direction of change, experimental method, etc.). This allows for more accuracyand the ability to drill down into the exact nature of a biological relationship—detailswhich are crucial for building relevant models and accelerating discoveryresearch."
 
 
Additionally, highly structured findings allow forcomputation and semantic consistency—which means researchers can quickly findbetter, more relevant information, Bullock adds. 
 
 
"In addition to these structured literature findings, IPAintegrates quality-controlled information from select publicly availabledatabases, such as DrugBank, Clinicaltrials.gov, HMDB, TarBase and manyothers," she says.
 
 
Bullock acknowledges that there is still a significanthurdle for researchers when it comes to interpreting data, accessinghigh-quality scientific information, and sharing that information. IPA will beused to analyze data and help researchers access relevant, detailed andaccurate knowledge that can be leveraged throughout the experimental lifecycle, she points out.
 
"For example, IPA can be used to create a testable modelthat will inform assay design," Bullock says. "Once data is generated, IPA willenhance QFAB's existing platform by helping researchers uncover novel insightsfrom their data by quickly identifying relationships, mechanisms, functions andpathways of relevance. QFAB researchers will now be able to quickly integrateand understand multiple lines of experimental evidence—either publiclyavailable or proprietary data—such as gene expression signatures, miRNAs andSNPs to identify common pathways or molecular mechanisms at the core of therespective experimental model."
 
 
Ultimately, the partnership will enable the research teamssupported by QFAB to use IPA to make better, knowledge-based decisions, Bullocksays.
 
 
"Specifically, with regard to translational medicineefforts, IPA can help researchers understand mechanisms of disease, identifygenes and proteins associated with the etiology of a specific disease andpredict and validate biomarkers," she says.
 
 
Barker says that while the partnership may not help datamanagement challenges, it will provide the opportunity for research programs toaccess an important analytical tool in the process of understanding thebiological pathways involved in their specific areas of interest.   
 
 
"Visualization of these pathways is a key opportunity forthe scientist in identifying areas of interest," Barker concludes."Multidisciplinary research of this type relies heavily on the availability ofcomputational systems to mine high-throughput datasets collected from disparatechemistry and genomics platforms, advanced visualization of pathways andnetworks, and systems to share results. All these functions are to be providedby the proposed platform. IPA is a key part of that functionality."

 
IPA to support multiple QFAB projects

Jeremy Barker, CEO of the Queensland Facility for AdvancedBioinformatics (QFAB), says Ingenuity Systems' IPA will support a number ofresearch programs that the consortium in engaged in which seek which tocharacterize and understand the complex biomolecular networks that controlbiological processes in cells, tissues or whole organisms.
 
For example, inference and computational analysis ofbiomolecular networks and systems in mammalian cells is a core objective of oneof QFAB's collaborators, Barker says. Two of their four research programs haveas primary aims the inference, analysis, modeling and visualization of cellularregulatory networks. 
 
 
Another research project that QFAB is working closely ininvolves the investigation of large-scale expression data from normal breastand cancer cell lines for inference of nuclear receptor networks, with the goalof identifying and validating new potential targets for cancer treatment,Barker says.
 
In addition, a key collaborator at the Institute forMolecular Bioscience at the University of Queensland uses IPA and is looking toextend his research through access to the systems biology platform by allowingthe systematic linkage and display of expression patterns of all components ofthe regulatory network in normal and transformed cell types throughout the cellcycle, including canonical and variant phosphoregulator genes generated byalternative transcription events to identify candidate gene products that drivekey phenotypes in model systems.
 
 
"Capturing the information contained within the transcriptomeand modeling transcriptome dynamics to identify key genes and transcriptionalprograms is a central research theme of this work," Barker adds.
 
 
The Systems Biology Platform will also enable the researchconducted by a collaborator based at the Mater Hospital to systematicallyintegrate a broad range of data in the context of ligand-receptor function andsignal transduction pathways in metabolism, leading to the identification ofmolecular and physiological factors involved in obesity and related diseases,Barker adds.
 
 
Finally, researchers at the Eskitis Institute intend to usethe platform to investigate the natural variation of genetic networks in thehuman populations, elucidate associations between genotype and genetic networksand identify leads into complex diseases such as schizophrenia and Parkinson'sdisease, Barker says.

Amy Swinderman

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